Pixel Recurrent Neural Networks 和 autoregressive models 自迴歸模型
Pixel Recurrent Neural Networks pixel rnn 是 生成模型的一種，基於autoregressive models。他的思想很簡單，就是最大似然估計的方式去擬合圖像數據。將二維的圖像數據比作序列數據，以條件概率的方式，逐點預測和計算。並且每個像素點的預測都在[0-255]之間，（單通道情況下）如下圖1所示： 圖1，autoregressive models 在二
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相關文章
- 1. 【生成模型】Pixel Recurrent Neural Networks翻譯
- 2. 生成模型之Pixel Recurrent Neural Networks
- 3. Sequence Models(Week1)---Recurrent Neural Networks
- 4. Lecture 6: Language Models and Recurrent Neural Networks
- 5. CS224n-08 Recurrent Neural Networks and Language Models
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- 10. (21)[ICML16] PixelRNN：Pixel Recurrent Neural Networks